Search Results (1,166)

Although social media influencers (SMIs) play a pivotal role in destination marketing, the underlying factors through which they shape tourists’ interest and travel intentions remain underexplored. Based on the modified attention interest desire action (AIDA) model, this study addresses this gap by investigating how the characteristics of SMIs influence travel intentions through destination perceived trust and destination perceived attractiveness. A total of 416 valid questionnaires were analyzed using partial least squares structural equation modeling (PLS-SEM) and an artificial neural network (ANN). The results revealed that SMIs’ similarity, expertise, physical attractiveness, social attractiveness, sincerity, and visibility enhanced tourists’ destination perceived trust and destination perceived attractiveness, thereby influencing travel intentions. Additionally, the ANN analysis complements the PLS-SEM results by comparing predictive performance and identifying the relative importance of SMI characteristics. These findings provide several suggestions for destination management organizations to improve influencer marketing. Full article

Volcanic caves, commonly referred to as lava tubes, are typically shallow subsurface cavities formed by the cooling of a generally basaltic lava flow under a roof or crust that cools faster and acts as a thermal insulator. These cavities can serve as tourist attractions, in which case their stability must be analyzed and ensured. Empirical rock mass classification systems, in this case we have applied the Q-index have been employed to evaluate the stability of underground excavations: mines and tunnels, including natural caves. We have identified that these approaches have limitations, particularly incorporating key geometric parameters such as roof thickness and cave length. In this study we have analyzed applicability of the Scaled Span Method (SSM) to volcanics caves. This method was originally developed for the stability assessment of crown pillar stability in shallow mines. We have developed a dataset of lava tubes (caves) located in the Canary Islands (Spain), the Galápagos Islands (Ecuador), and Jordan. In this research we have conducted geomechanical characterization using the Q-system, and also the Scaled Span to evaluate stability based on cave geometry and rock mass properties. The results indicate that, in general, the SSM yields more conservative stability estimates compared to the Q-system, particularly for shallow caves with limited roof thickness. Nevertheless, discrepancies between the two approaches are observed in several cases, highlighting the limitations of directly transferring empirical methods developed for mining excavations to natural cave systems. These differences underscore the need for careful interpretation and, where appropriate, complementary stability analyses. The Scaled Span Method is useful for preliminary assessment of volcanic cave stability, especially in scenarios where potential interaction with the ground surface is expected: buildings or roads on top. However, its application requires adaptation and critical evaluation due to the fundamental differences between engineered mining excavations and natural subsurface cavities. Full article

Existing self-driving itinerary planning systems rely on single-objective optimization and static cost estimation, limiting their ability to accommodate diverse user preferences and dynamic price fluctuations. Methods: This study presents an interactive itinerary planning system formulated as a Tourist Trip Design Problem (TTDP) with subset selection, integrating an improved NSGA-II algorithm for simultaneous optimization of travel time, cost, and experiential quality, a WPGA-based combined prediction model for dynamic cost forecasting, and a human-in-the-loop interface for real-time preference adjustment. Results: Evaluated on 30 Hainan Island attractions under a 7-day/6-night scenario with 30 independent runs, the improved NSGA-II selects 8.9 ± 1.0 stops with total time 26.2 ± 4.7 h, cost CNY 1526 ± 356, and experience index 36.69 ± 5.60, with backend optimization latency 0.5 ± 0.1 s (end-to-end user-perceived latency including network and frontend rendering: 1.8 s). Compared with standard NSGA-II, the improved version achieves 114.0% higher aggregate experience index while selecting more stops (8.9 vs. 4.2); this improvement is primarily driven by the larger number of selected stops, and normalized indicators (experience per stop: 4.12 vs. 4.08) provide a more balanced interpretation of the trade-offs. The cost model covers three categories (fuel, tickets, and hotel), with the optimization objective f2 capturing route-dependent costs (fuel + tickets) and the hotel treated as a fixed baseline. However, empirical validation is restricted to two geographic corridors. Full article

This paper proposes a hybrid content-based recommender system aimed at enhancing personalized tourism experiences and supporting the promotion of tourism in Morocco, with particular emphasis on the Drâa-Tafilalet region. The proposed approach integrates three machine learning models—Decision Tree, k-nearest neighbors, and Support Vector Machine—to predict user ratings for historical tourism sites. Tourist attraction metadata and user-generated reviews are represented using TF-IDF vectorization, while the predictions produced by the individual models are combined through an inverse-error weighting strategy. The system is evaluated using two datasets: a subset of the Yelp dataset comprising reviews of historical buildings in the United States, and a regional Drâa-Tafilalet dataset. Experimental results, assessed using MAE and RMSE, indicate that the weighted hybrid model outperforms the individual recommendation models by achieving lower prediction errors. These findings demonstrate the potential of hybrid content-based recommendation approaches to improve the accuracy of personalized tourism recommendations, support tourist decision-making, and promote underrepresented regional destinations. Full article

Sicily is a Mediterranean island region whose economy is based especially on tourism, with tourists being attracted to its beaches. The whole coastline of the island, including its minor islands, is 1745 km. At the moment, considering the whole period analyzed by the Coastal Plan of Sicilian Region (2008–2024), about 115 km of the 683 km of the main island’s sandy coastline present erosion problems that affect 23% of its unprotected coastline (506 km). Some of these problems are threatening Sicily’s economic and important historical assets as well as its cultural heritage; 177 km of protected beaches, using hard structure, have lost their original beauty. In the last fifty years, about 2.5 km² of beaches were lost due to erosion, causing damages worth approximately 5 billion Euros. Current coastal management guidelines identify artificial beach nourishment as the most sustainable strategy for protecting the insular economy against the accelerating impacts of climate change. Successful nourishment, however, hinges on the availability of vast quantities of borrow material that must be granulometrically, compositionally, and chromatically compatible with native beach sediments. While subaerial quarries are being phased out due to their irreversible environmental degradation and logistical inefficiency, as well as local “ephemeral” sources (such as harbor dredging or over-alluvial deposits) providing insufficient volumes, the research has shifted toward Remote/Relict Marine Sediment Deposits (RMSDs). This study evaluates the strategic potential of RMSDs as a high-volume, low-impact resource for coastal defense. By integrating the geological, morphological, and sedimentological characteristics of the Sicilian continental shelf within a GIS framework, we have delineated potential dredging sectors. These areas are bounded by the −30 m isobath (the lower limit of Posidonia oceanica meadows) and the −200 m isobath, which represents the current operational limit of Jumbo Trailer Suction Hopper Dredgers (TSHDs). A multi-criteria constraint analysis was performed, categorizing environmental and infrastructural overlaps into fatal flaws (prohibitive) and non-prohibitive constraints. This subtractive spatial analysis reveals that approximately 6500 km² of the Sicilian shelf may be eligible for resource exploitation concessions, pending site-specific, high-resolution surveys. Full article

The aim of this article is to demonstrate the significance of Iceland’s Ring Road as a key route providing access to geotourism attractions and to discuss its role in shaping visitor traffic in the context of tourist feedback and the principles of sustainable tourism development. The study is based on an analysis of 223 online reviews concerning the Ring Road, supplemented by the author’s own field observations from travelling around Iceland. Opinions relating to natural and anthropogenic assets, tourist infrastructure, transport accessibility, travel safety, visitor concentration and the interpretation of geological heritage were analysed. The results indicate that the Ring Road is highly rated by tourists, primarily because of the exceptional natural assets located along and near the route. At the same time, the analysis revealed challenges related to traffic concentration at the most recognisable attractions, the uneven quality of tourist infrastructure, high costs, travel safety and the limited use of the educational potential of geosites. The findings show that online reviews, when combined with field observations, can serve as a useful source of knowledge about the practical conditions for the sustainable use of geotourism attractions in popular natural destinations. Full article

Agritourism farm-stay guesthouses represent a burgeoning sector of rural tourism, wherein locally produced food serves as the primary experiential attraction. This study examines tourist perceptions regarding food quality, sensory characteristics, sustainability awareness, loyalty indicators, and comparative evaluations at three farm-stay guesthouses in Caraș-Severin County, Romania, located at distinct altitudes: lowland (Sacu, 154 m a.s.l.), hill (Văliug, 550 m a.s.l.), and mountain (Cozia, 1130 m a.s.l.). Altitude in this study marks three distinct settings—lowland, hill, mountain—rather than functioning as a tested independent variable. The results show that tourists evaluated all three guesthouses similarly, with no statistically significant differences across zones. The comparative design was a way of asking whether own-farm food quality perceptions hold across different agritourism contexts, not a test of what altitude does to those perceptions. A structured questionnaire (n = 650) was distributed to guests following an informed consent protocol. Four latent constructs were operationalised: food quality (FQ; Cronbach’s α = 0.593), sensory characteristics (SCs; α = 0.596), sustainability perception (SP; α = 0.393), and comparison with non-farm establishments (CF; α = 0.621). Overall gastronomic satisfaction was particularly high (mean = 4.71 ± 0.62 on a 1–5 Likert scale), and the average overall score was 9.44 ± 1.01 out of 10. Multiple regression accounted for 7.5% of the satisfaction variance (R² = 0.075; F(4,643) = 13.09, p < 0.001), with sensory characteristics (β = 0.232, p < 0.001) and sustainability perception (β = 0.088, p = 0.020) serving as significant predictors. Food origin transparency substantially impacted satisfaction (ANOVA: F(3,646) = 4.964, p = 0.002): visitors who received thorough provenance explanations were more satisfied (mean = 4.77) than those who received no information (mean = 4.57). Among the 569 respondents with prior non-farm experience, 85.2% rated farm-stay cuisine as superior to non-farm alternatives overall. Food quality perceptions in these three Caraș-Severin guesthouses are uniformly high regardless of altitude. What separates more satisfied guests from less satisfied ones is not the measurable quality of the product but whether the host explained where it came from. Full article

As night tourism has become a key driver of the nighttime economy in Chinese cities, urban lighting landscapes—as core attractions for night tourism—call for systematic investigation into the relationship between their development effectiveness and visitor experience. However, existing studies have primarily focused on design strategies or economic value, lacking in-depth exploration of visitor experience based on large-scale online review data. Furthermore, the integrated analysis of sentiment analysis and topic modeling for online reviews remains insufficient, making it difficult to uncover the dimensional differences underlying different sentiment types. Therefore, this study employs a hybrid BERT-LDA model to conduct a collaborative analysis of 45,768 valid tourism online reviews covering 30 urban lighting landscapes in China. First, the pre-trained Bidirectional Encoder Representations from Transformers (BERT) model identified the sentiment orientation of each review. Subsequently, the Latent Dirichlet Allocation (LDA) model extracted latent topics from positive and negative reviews separately. Research findings indicate that tourists generally hold positive attitudes toward urban lighting landscapes. Specifically, five positive topics and three negative topics were extracted from the review corpus. This study fills a research gap in the field of urban lighting landscapes and reveals the underlying demands of Chinese tourists regarding such landscapes from a demand-side perspective, thereby providing a decision-making basis for optimizing the planning and design of urban lighting landscapes. Full article

The research scope comprises the analysis of disjunctions between photographic representations, architectural landmarks, tourist icons, and urbanized surroundings. Given the problem posed by imagery distortions in human cognition, the guiding hypothesis is that the perception of scenes of constructed touristic attractions is distorted with respect to their associated built vicinities. Therefore, the general objective is to systematize guidelines for integrating public policies on visual communication and urban management. Using multi-method, applied, qualitative–quantitative, and exploratory approaches, an investigation is conducted in four main parts: a literature review highlighting knowledge gaps on the topic; procedural methods involving the selection of study areas (cities) and objects (architectures) from those most visited worldwide in the pre-pandemic period followed by submitting their representative photographs for interpretation by experts and the public; analysis involving interpreting respondents’ feedback in association with specific criteria; and an integrated discussion leading to the formulation of directives. As a synthesis of the answers to the research question, the results diagnose a misrepresentation of the immediate and nearby surroundings of architectural sites due to the exclusive observation of images published on official tourism websites, confirming the proposed hypothesis and concluding that the methodological essay is feasible, with case-specific adaptations, as a reference for adequately conveying touristic landscapes in contemporary cities. Full article

In the post-Olympic era, China’s ice and snow tourism is shifting toward an experience-oriented model. Taking the Chongli Ice and Snow Tourism Resort as a case study, this research applies a BERTopic-LLM framework, BERT-based sentiment analysis, and the IPA-Kano model to multi-platform user-generated content (UGC). We systematically examined tourists’ perceptual structures, spatial experiential differences, and nonlinear needs. The results indicate that while overall tourist sentiments are positive, substantial spatial and perceptual heterogeneity exists. Positive perceptions are primarily driven by high-quality core attractions (ski slopes and Olympic heritage), whereas negative perceptions stem from operational issues like peak-season congestion, inflated prices, and insufficient service. Based on these characteristics, the resort’s spatial units are categorized into resource-integrated, facility-oriented, and core-attraction mismatch areas. The findings demonstrate that tourist satisfaction is non-linearly conditioned by the quality of supporting infrastructure rather than just resource endowment. Accordingly, we propose three optimization strategies—strengthening service guarantees, enhancing experiential value, and promoting cultural transformation—to support the sustainable development of China’s ice and snow tourism destinations. Full article

Understanding the spatial hierarchy, distribution patterns, and driving mechanisms of A-level tourist attractions is essential for optimizing tourism resource allocation and promoting sustainable regional development. This study integrates core–periphery theory with a sustainability perspective to examine hierarchical differentiation of China’s A-level tourist attractions, using 15,699 POI data points collected in 2024 and applying the nearest neighbor index (NNI), kernel density estimation, spatial autocorrelation analysis, and the geographical detector model. The results indicate that these attractions exhibit an unbalanced spatial distribution characterized by a “dense east and sparse west” pattern, with the Hu Huanyong Line (Hu Line) as an important spatial boundary, showing east–west hierarchical disparities. The attractions demonstrate a clustered distribution pattern, although the degree of agglomeration decreases as attraction grades increase. Spatial associations exhibit a pattern of coordination in eastern regions and polarization in western regions, forming a three-tier spatial hierarchy of core–sub-core–periphery. Population density exhibits the strongest explanatory power. Interaction detector results reveal grade-dependent differences. 2A attractions show weak factor associations, whereas 5A attractions are more strongly linked to resource endowment, population density, and economic development. These findings advance the theoretical understanding of the hierarchical spatial structure and differentiated development mechanisms of tourist attractions. Full article

The rapid advancement of internet technology has transformed the tourism industry from traditional offline services to digital networked, and intelligent platforms. WebGIS has become critical infrastructure for tourism information retrieval and spatial decision-making. However, the growing volume and heterogeneity of multi-source tourism data expose fundamental limitations in conventional relational database architectures, particularly in handling complex spatial semantic queries. To address this, the present study proposes a WebGIS design methodology that integrates knowledge graphs with relational databases through a dual-database collaborative architecture. Using tourist attraction data from China’s Xinjiang Uyghur Autonomous Region as a case study, a prototype Xinjiang Smart Tourism WebGIS system was constructed, which consists of an asynchronous synchronization mechanism based on Change Data Capture (CDC) to ensure data consistency across heterogeneous databases. Subsequently, tourism semantic queries of varying depths were constructed and comprehensively tested across different data scales. The experimental results indicate that the proposed methodology effectively decouples business transactions and supports complex relationship computations, achieving shorter cross-domain semantic query times and higher latency stability. These findings offer practical guidance for designing high-performance regional tourism information services. Full article

Tourism development potential and observed development performance do not necessarily evolve synchronously, particularly in old industrial and restructuring regions where attraction supply, market linkage, and visitor experience may be spatially uneven. This study develops a multi-source diagnostic framework for identifying tourism potential–performance mismatch across the 14 prefecture-level cities of Liaoning Province, China. Drawing on Ctrip review texts, rating scores, timestamps, platform-displayed reviewer-origin labels, A-level scenic-spot point data, and annual official city-level tourism statistics, the study constructs three dimension-specific sub-indices—the Scenic Experience Index (ESI), the Market Linkage Index (MLI), and the Attraction Foundation Index (AFI)—and synthesizes them into a Comprehensive Potential Index (CPI). The CPI is then compared with an Observed Performance Index (OPI) constructed from domestic tourist arrivals and domestic tourism revenue for 2016–2022. The results show that attraction foundation contributes most strongly to composite tourism potential, while market linkage and scenic experience condition how this structural basis is associated with observed outcomes. The CPI–OPI comparison identifies three relationship types: matched, potential-leading, and performance-leading cities. Dalian and Shenyang are high-level matched cities, Benxi and Jinzhou are high-potential but under-converted cities, and Anshan and Dandong are performance-leading cities. These findings demonstrate that favorable structural tourism conditions are not automatically transformed into realized market performance. The study contributes a multidimensional, gap-analysis-based diagnostic architecture that can support tourism-related spatial planning and territorial governance in transitional regions. Full article

Walking tourism is an important form of thematic and sustainable tourism, especially in rural and naturally attractive destinations. It contributes to diversifying the tourist environments and improving destination management. This paper analyses the role of walking tourism in destination management and uses an integrated machine-learning model to predict tourist preferences. A key focus of this study is identifying the key factors influencing walking tourism preferences, including demographic, socioeconomic, behavioural, and activity-related variables. The methodology of this study is based on an integrated Machine Learning (ML) approach. CatBoostClassifier was used as the primary predictive model, and hyperparameter optimization was performed using Particle Swarm Optimization (PSO). Model interpretability was ensured through SHapley Additive exPlanations (SHAP) analysis, supported by CatBoost feature importance evaluation. This combination enables both high prediction accuracy and transparent explanation of variable influence. The research is based on 467 responses collected through an anonymous online survey. Results confirm that walking tourism is predominantly linked to natural and mountain experiences, which have strong implications for destination planning and tourism product development. The proposed model provides reliable predictions of tourist preferences under class imbalance conditions, achieving a macro-F1 score of 0.5114. Additionally, key factors influencing the choice of walking tours were identified, supporting destination managers in tourist segmentation, tourism product development, and sustainable allocation of destination resources. Full article

This study aimed to systematically categorize and critically analyze the feasibility of developing a cultural resource-based tourism route in Betong District, Yala Province, the southernmost area of Thailand, which is called “the city in the mist.” Research and development techniques were employed using a simulated map from an information system and community forums to create and revise a cultural resource-based tourism map in these areas: the Aiyoeweng, Tano Maero, Betong, and Than Nam Thip Subdistricts. The participants from five communities, 10 people per community, totaling 50 participants, were selected through purposive sampling to join in drafting a cultural resource map by pinpointing important areas in each subdistrict. The fieldwork data collected in each subdistrict were categorized and the content was analyzed to examine the feasibility of the approach to creating a map based on cultural resources. The results found that the tourism patterns resulting from a strong resource base could be divided into tangible and intangible cultural resources. The selected resources include local food, learning centers, tourist attractions, interesting entertainment activities, and community service centers. These were then used to create a simulated map, which was analyzed to determine the feasibility of a tourism route based on resource capital, abundant forests, cultural capital in historical sites, and social capital that were covered in community tourism policies, plans, and guidelines for tourism management to achieve maximum benefits, resulting from the community process that had to jointly design the process. The results of this study are part of the restoration of tourism based on resources for income management and for local organizations to expand and upgrade tourism to the regional economic zones in the southern border provinces. Full article